Overview

Dataset statistics

Number of variables40
Number of observations45379
Missing cells67148
Missing cells (%)3.7%
Total size in memory13.8 MiB
Average record size in memory320.0 B

Variable types

Text11
Numeric29

Alerts

Science Fiction has constant value ""Constant
History has constant value ""Constant
belongs_to_collection has 40890 (90.1%) missing valuesMissing
overview has 941 (2.1%) missing valuesMissing
tagline has 24980 (55.0%) missing valuesMissing
popularity is highly skewed (γ1 = 29.21581948)Skewed
return is highly skewed (γ1 = 138.3340992)Skewed
budget has 36493 (80.4%) zerosZeros
TV Movie has 44612 (98.3%) zerosZeros
Western has 44337 (97.7%) zerosZeros
Documentary has 41458 (91.4%) zerosZeros
Music has 43781 (96.5%) zerosZeros
Foreign has 43758 (96.4%) zerosZeros
War has 44056 (97.1%) zerosZeros
Mystery has 42915 (94.6%) zerosZeros
Science Fiction has 45379 (100.0%) zerosZeros
History has 45379 (100.0%) zerosZeros
Horror has 40708 (89.7%) zerosZeros
Thriller has 37759 (83.2%) zerosZeros
Crime has 41074 (90.5%) zerosZeros
Action has 38785 (85.5%) zerosZeros
Drama has 25123 (55.4%) zerosZeros
Romance has 38646 (85.2%) zerosZeros
Fantasy has 43066 (94.9%) zerosZeros
Adventure has 41885 (92.3%) zerosZeros
Family has 42611 (93.9%) zerosZeros
Comedy has 32198 (71.0%) zerosZeros
Animation has 43446 (95.7%) zerosZeros
revenue has 37972 (83.7%) zerosZeros
runtime has 1535 (3.4%) zerosZeros
vote_average has 2947 (6.5%) zerosZeros
vote_count has 2849 (6.3%) zerosZeros
return has 39998 (88.1%) zerosZeros

Reproduction

Analysis started2023-06-29 22:28:30.182458
Analysis finished2023-06-29 22:28:36.714495
Duration6.53 seconds
Software versionydata-profiling vv4.3.1
Download configurationconfig.json

Variables

belongs_to_collection
Text

MISSING 

Distinct1695
Distinct (%)37.8%
Missing40890
Missing (%)90.1%
Memory size354.6 KiB
2023-06-29T19:28:36.818495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length184
Median length167
Mean length141.4900869
Min length75

Characters and Unicode

Total characters635149
Distinct characters170
Distinct categories13 ?
Distinct scripts7 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique390 ?
Unique (%)8.7%

Sample

1st row{'id': 10194, 'name': 'Toy Story Collection', 'poster_path': '/7G9915LfUQ2lVfwMEEhDsn3kT4B.jpg', 'backdrop_path': '/9FBwqcd9IRruEDUrTdcaafOMKUq.jpg'}
2nd row{'id': 119050, 'name': 'Grumpy Old Men Collection', 'poster_path': '/nLvUdqgPgm3F85NMCii9gVFUcet.jpg', 'backdrop_path': '/hypTnLot2z8wpFS7qwsQHW1uV8u.jpg'}
3rd row{'id': 96871, 'name': 'Father of the Bride Collection', 'poster_path': '/nts4iOmNnq7GNicycMJ9pSAn204.jpg', 'backdrop_path': '/7qwE57OVZmMJChBpLEbJEmzUydk.jpg'}
4th row{'id': 645, 'name': 'James Bond Collection', 'poster_path': '/HORpg5CSkmeQlAolx3bKMrKgfi.jpg', 'backdrop_path': '/6VcVl48kNKvdXOZfJPdarlUGOsk.jpg'}
5th row{'id': 117693, 'name': 'Balto Collection', 'poster_path': '/w0ZgH6Lgxt2bQYnf1ss74UvYftm.jpg', 'backdrop_path': '/9VM5LiJV0bGb1st1KyHA3cVnO2G.jpg'}
ValueCountFrequency (%)
name 4495
 
9.7%
id 4489
 
9.7%
poster_path 4489
 
9.7%
backdrop_path 4489
 
9.7%
collection 3744
 
8.1%
none 1771
 
3.8%
the 1146
 
2.5%
of 230
 
0.5%
series 147
 
0.3%
139
 
0.3%
Other values (6631) 21071
45.6%
2023-06-29T19:28:37.109532image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 59197
 
9.3%
41722
 
6.6%
p 29065
 
4.6%
a 25697
 
4.0%
o 25031
 
3.9%
e 24216
 
3.8%
t 23190
 
3.7%
: 18055
 
2.8%
n 16720
 
2.6%
r 15819
 
2.5%
Other values (160) 356437
56.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 316950
49.9%
Other Punctuation 105717
 
16.6%
Uppercase Letter 94998
 
15.0%
Decimal Number 56923
 
9.0%
Space Separator 41722
 
6.6%
Connector Punctuation 8978
 
1.4%
Open Punctuation 4824
 
0.8%
Close Punctuation 4824
 
0.8%
Dash Punctuation 162
 
< 0.1%
Other Letter 37
 
< 0.1%
Other values (3) 14
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 29065
 
9.2%
a 25697
 
8.1%
o 25031
 
7.9%
e 24216
 
7.6%
t 23190
 
7.3%
n 16720
 
5.3%
r 15819
 
5.0%
i 15328
 
4.8%
h 14433
 
4.6%
d 13697
 
4.3%
Other values (69) 113754
35.9%
Uppercase Letter
ValueCountFrequency (%)
C 7691
 
8.1%
N 5092
 
5.4%
T 4595
 
4.8%
S 4188
 
4.4%
A 3722
 
3.9%
M 3695
 
3.9%
B 3679
 
3.9%
D 3679
 
3.9%
L 3481
 
3.7%
G 3459
 
3.6%
Other values (33) 51717
54.4%
Other Letter
ValueCountFrequency (%)
3
 
8.1%
3
 
8.1%
3
 
8.1%
3
 
8.1%
3
 
8.1%
3
 
8.1%
3
 
8.1%
3
 
8.1%
3
 
8.1%
2
 
5.4%
Other values (4) 8
21.6%
Other Punctuation
ValueCountFrequency (%)
' 59197
56.0%
: 18055
 
17.1%
, 13546
 
12.8%
. 7379
 
7.0%
/ 7228
 
6.8%
" 214
 
0.2%
& 52
 
< 0.1%
! 35
 
< 0.1%
* 4
 
< 0.1%
? 4
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 6788
11.9%
2 6105
10.7%
3 5870
10.3%
4 5779
10.2%
5 5699
10.0%
9 5476
9.6%
8 5450
9.6%
6 5367
9.4%
7 5345
9.4%
0 5044
8.9%
Open Punctuation
ValueCountFrequency (%)
{ 4489
93.1%
( 330
 
6.8%
[ 5
 
0.1%
Close Punctuation
ValueCountFrequency (%)
} 4489
93.1%
) 330
 
6.8%
] 5
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 160
98.8%
2
 
1.2%
Space Separator
ValueCountFrequency (%)
41722
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8978
100.0%
Final Punctuation
ValueCountFrequency (%)
9
100.0%
Modifier Letter
ValueCountFrequency (%)
3
100.0%
Other Number
ValueCountFrequency (%)
½ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 411534
64.8%
Common 223164
35.1%
Cyrillic 414
 
0.1%
Hiragana 15
 
< 0.1%
Hangul 10
 
< 0.1%
Katakana 9
 
< 0.1%
Han 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 29065
 
7.1%
a 25697
 
6.2%
o 25031
 
6.1%
e 24216
 
5.9%
t 23190
 
5.6%
n 16720
 
4.1%
r 15819
 
3.8%
i 15328
 
3.7%
h 14433
 
3.5%
d 13697
 
3.3%
Other values (70) 208338
50.6%
Cyrillic
ValueCountFrequency (%)
л 48
 
11.6%
и 41
 
9.9%
о 37
 
8.9%
к 30
 
7.2%
е 27
 
6.5%
я 25
 
6.0%
а 17
 
4.1%
К 16
 
3.9%
ц 16
 
3.9%
р 14
 
3.4%
Other values (32) 143
34.5%
Common
ValueCountFrequency (%)
' 59197
26.5%
41722
18.7%
: 18055
 
8.1%
, 13546
 
6.1%
_ 8978
 
4.0%
. 7379
 
3.3%
/ 7228
 
3.2%
1 6788
 
3.0%
2 6105
 
2.7%
3 5870
 
2.6%
Other values (24) 48296
21.6%
Hiragana
ValueCountFrequency (%)
3
20.0%
3
20.0%
3
20.0%
3
20.0%
3
20.0%
Hangul
ValueCountFrequency (%)
2
20.0%
2
20.0%
2
20.0%
2
20.0%
2
20.0%
Katakana
ValueCountFrequency (%)
3
33.3%
3
33.3%
3
33.3%
Han
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 634435
99.9%
Cyrillic 414
 
0.1%
None 246
 
< 0.1%
Hiragana 15
 
< 0.1%
Punctuation 14
 
< 0.1%
Katakana 12
 
< 0.1%
Hangul 10
 
< 0.1%
CJK 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 59197
 
9.3%
41722
 
6.6%
p 29065
 
4.6%
a 25697
 
4.1%
o 25031
 
3.9%
e 24216
 
3.8%
t 23190
 
3.7%
: 18055
 
2.8%
n 16720
 
2.6%
r 15819
 
2.5%
Other values (71) 355723
56.1%
Cyrillic
ValueCountFrequency (%)
л 48
 
11.6%
и 41
 
9.9%
о 37
 
8.9%
к 30
 
7.2%
е 27
 
6.5%
я 25
 
6.0%
а 17
 
4.1%
К 16
 
3.9%
ц 16
 
3.9%
р 14
 
3.4%
Other values (32) 143
34.5%
None
ValueCountFrequency (%)
é 45
18.3%
ä 40
16.3%
ô 35
14.2%
ò 28
11.4%
ö 19
7.7%
ó 14
 
5.7%
ı 14
 
5.7%
í 9
 
3.7%
á 4
 
1.6%
İ 4
 
1.6%
Other values (19) 34
13.8%
Punctuation
ValueCountFrequency (%)
9
64.3%
3
 
21.4%
2
 
14.3%
Katakana
ValueCountFrequency (%)
3
25.0%
3
25.0%
3
25.0%
3
25.0%
Hiragana
ValueCountFrequency (%)
3
20.0%
3
20.0%
3
20.0%
3
20.0%
3
20.0%
CJK
ValueCountFrequency (%)
3
100.0%
Hangul
ValueCountFrequency (%)
2
20.0%
2
20.0%
2
20.0%
2
20.0%
2
20.0%

budget
Real number (ℝ)

ZEROS 

Distinct1223
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4232324.568
Minimum0
Maximum380000000
Zeros36493
Zeros (%)80.4%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:37.253494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile25000000
Maximum380000000
Range380000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation17439317.02
Coefficient of variation (CV)4.120505584
Kurtosis66.63900958
Mean4232324.568
Median Absolute Deviation (MAD)0
Skewness7.118579439
Sum1.920586566 × 1011
Variance3.04129778 × 1014
MonotonicityNot monotonic
2023-06-29T19:28:37.387496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36493
80.4%
5000000 286
 
0.6%
10000000 259
 
0.6%
20000000 243
 
0.5%
2000000 242
 
0.5%
15000000 226
 
0.5%
3000000 223
 
0.5%
25000000 206
 
0.5%
1000000 197
 
0.4%
30000000 190
 
0.4%
Other values (1213) 6814
 
15.0%
ValueCountFrequency (%)
0 36493
80.4%
1 25
 
0.1%
2 14
 
< 0.1%
3 9
 
< 0.1%
4 8
 
< 0.1%
ValueCountFrequency (%)
380000000 1
 
< 0.1%
300000000 1
 
< 0.1%
280000000 1
 
< 0.1%
270000000 1
 
< 0.1%
260000000 3
< 0.1%

TV Movie
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01690209128
Minimum0
Maximum1
Zeros44612
Zeros (%)98.3%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:37.502495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1289060773
Coefficient of variation (CV)7.626634787
Kurtosis54.18757167
Mean0.01690209128
Median Absolute Deviation (MAD)0
Skewness7.495677651
Sum767
Variance0.01661677676
MonotonicityNot monotonic
2023-06-29T19:28:37.595525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 44612
98.3%
1 767
 
1.7%
ValueCountFrequency (%)
0 44612
98.3%
1 767
 
1.7%
ValueCountFrequency (%)
1 767
 
1.7%
0 44612
98.3%

Western
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02296216312
Minimum0
Maximum1
Zeros44337
Zeros (%)97.7%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:37.687495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1497845005
Coefficient of variation (CV)6.523100621
Kurtosis38.57778855
Mean0.02296216312
Median Absolute Deviation (MAD)0
Skewness6.369936287
Sum1042
Variance0.02243539658
MonotonicityNot monotonic
2023-06-29T19:28:37.782495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 44337
97.7%
1 1042
 
2.3%
ValueCountFrequency (%)
0 44337
97.7%
1 1042
 
2.3%
ValueCountFrequency (%)
1 1042
 
2.3%
0 44337
97.7%

Documentary
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08640560612
Minimum0
Maximum1
Zeros41458
Zeros (%)91.4%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:37.881496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2809651526
Coefficient of variation (CV)3.251700499
Kurtosis6.668767757
Mean0.08640560612
Median Absolute Deviation (MAD)0
Skewness2.944227207
Sum3921
Variance0.07894141695
MonotonicityNot monotonic
2023-06-29T19:28:37.976525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 41458
91.4%
1 3921
 
8.6%
ValueCountFrequency (%)
0 41458
91.4%
1 3921
 
8.6%
ValueCountFrequency (%)
1 3921
 
8.6%
0 41458
91.4%

Music
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03521452654
Minimum0
Maximum1
Zeros43781
Zeros (%)96.5%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:38.070495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.184323662
Coefficient of variation (CV)5.234307545
Kurtosis23.43658602
Mean0.03521452654
Median Absolute Deviation (MAD)0
Skewness5.043367238
Sum1598
Variance0.03397521236
MonotonicityNot monotonic
2023-06-29T19:28:38.161532image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 43781
96.5%
1 1598
 
3.5%
ValueCountFrequency (%)
0 43781
96.5%
1 1598
 
3.5%
ValueCountFrequency (%)
1 1598
 
3.5%
0 43781
96.5%

Foreign
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03572136892
Minimum0
Maximum1
Zeros43758
Zeros (%)96.4%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:38.254524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1855966373
Coefficient of variation (CV)5.195675389
Kurtosis23.03416264
Mean0.03572136892
Median Absolute Deviation (MAD)0
Skewness5.003313647
Sum1621
Variance0.03444611179
MonotonicityNot monotonic
2023-06-29T19:28:38.344495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 43758
96.4%
1 1621
 
3.6%
ValueCountFrequency (%)
0 43758
96.4%
1 1621
 
3.6%
ValueCountFrequency (%)
1 1621
 
3.6%
0 43758
96.4%

War
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0291544547
Minimum0
Maximum1
Zeros44056
Zeros (%)97.1%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:38.437525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1682411847
Coefficient of variation (CV)5.770685351
Kurtosis29.33346972
Mean0.0291544547
Median Absolute Deviation (MAD)0
Skewness5.597515243
Sum1323
Variance0.02830509622
MonotonicityNot monotonic
2023-06-29T19:28:38.532525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 44056
97.1%
1 1323
 
2.9%
ValueCountFrequency (%)
0 44056
97.1%
1 1323
 
2.9%
ValueCountFrequency (%)
1 1323
 
2.9%
0 44056
97.1%

Mystery
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05429824368
Minimum0
Maximum1
Zeros42915
Zeros (%)94.6%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:38.625525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2266077581
Coefficient of variation (CV)4.1733902
Kurtosis13.47583475
Mean0.05429824368
Median Absolute Deviation (MAD)0
Skewness3.933858262
Sum2464
Variance0.05135107602
MonotonicityNot monotonic
2023-06-29T19:28:38.715524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 42915
94.6%
1 2464
 
5.4%
ValueCountFrequency (%)
0 42915
94.6%
1 2464
 
5.4%
ValueCountFrequency (%)
1 2464
 
5.4%
0 42915
94.6%

Science Fiction
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros45379
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:38.807531image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-29T19:28:38.889524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 45379
100.0%
ValueCountFrequency (%)
0 45379
100.0%
ValueCountFrequency (%)
0 45379
100.0%

History
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros45379
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:38.976495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-06-29T19:28:39.057495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 45379
100.0%
ValueCountFrequency (%)
0 45379
100.0%
ValueCountFrequency (%)
0 45379
100.0%

Horror
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1029330748
Minimum0
Maximum1
Zeros40708
Zeros (%)89.7%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:39.143525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3038747962
Coefficient of variation (CV)2.952158933
Kurtosis4.830458777
Mean0.1029330748
Median Absolute Deviation (MAD)0
Skewness2.613473911
Sum4671
Variance0.09233989175
MonotonicityNot monotonic
2023-06-29T19:28:39.234497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 40708
89.7%
1 4671
 
10.3%
ValueCountFrequency (%)
0 40708
89.7%
1 4671
 
10.3%
ValueCountFrequency (%)
1 4671
 
10.3%
0 40708
89.7%

Thriller
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1679190815
Minimum0
Maximum1
Zeros37759
Zeros (%)83.2%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:39.326494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3737985322
Coefficient of variation (CV)2.226063463
Kurtosis1.157315265
Mean0.1679190815
Median Absolute Deviation (MAD)0
Skewness1.77686923
Sum7620
Variance0.1397253427
MonotonicityNot monotonic
2023-06-29T19:28:39.417526image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 37759
83.2%
1 7620
 
16.8%
ValueCountFrequency (%)
0 37759
83.2%
1 7620
 
16.8%
ValueCountFrequency (%)
1 7620
 
16.8%
0 37759
83.2%

Crime
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09486767007
Minimum0
Maximum1
Zeros41074
Zeros (%)90.5%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:39.514495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2930353008
Coefficient of variation (CV)3.088884766
Kurtosis5.646564022
Mean0.09486767007
Median Absolute Deviation (MAD)0
Skewness2.765197129
Sum4305
Variance0.08586968752
MonotonicityNot monotonic
2023-06-29T19:28:39.602494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 41074
90.5%
1 4305
 
9.5%
ValueCountFrequency (%)
0 41074
90.5%
1 4305
 
9.5%
ValueCountFrequency (%)
1 4305
 
9.5%
0 41074
90.5%

Action
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1453095044
Minimum0
Maximum1
Zeros38785
Zeros (%)85.5%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:39.694527image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3524164996
Coefficient of variation (CV)2.425281822
Kurtosis2.052234811
Mean0.1453095044
Median Absolute Deviation (MAD)0
Skewness2.012993881
Sum6594
Variance0.1241973892
MonotonicityNot monotonic
2023-06-29T19:28:39.784525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 38785
85.5%
1 6594
 
14.5%
ValueCountFrequency (%)
0 38785
85.5%
1 6594
 
14.5%
ValueCountFrequency (%)
1 6594
 
14.5%
0 38785
85.5%

Drama
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4463738734
Minimum0
Maximum1
Zeros25123
Zeros (%)55.4%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:39.874495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4971213981
Coefficient of variation (CV)1.113688385
Kurtosis-1.9535354
Mean0.4463738734
Median Absolute Deviation (MAD)0
Skewness0.2157561127
Sum20256
Variance0.2471296844
MonotonicityNot monotonic
2023-06-29T19:28:39.964529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 25123
55.4%
1 20256
44.6%
ValueCountFrequency (%)
0 25123
55.4%
1 20256
44.6%
ValueCountFrequency (%)
1 20256
44.6%
0 25123
55.4%

Romance
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1483725953
Minimum0
Maximum1
Zeros38646
Zeros (%)85.2%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:40.057529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.355472858
Coefficient of variation (CV)2.395812093
Kurtosis1.914354668
Mean0.1483725953
Median Absolute Deviation (MAD)0
Skewness1.97845149
Sum6733
Variance0.1263609528
MonotonicityNot monotonic
2023-06-29T19:28:40.148495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 38646
85.2%
1 6733
 
14.8%
ValueCountFrequency (%)
0 38646
85.2%
1 6733
 
14.8%
ValueCountFrequency (%)
1 6733
 
14.8%
0 38646
85.2%

Fantasy
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05097071333
Minimum0
Maximum1
Zeros43066
Zeros (%)94.9%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:40.242496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2199403685
Coefficient of variation (CV)4.315034147
Kurtosis14.6745667
Mean0.05097071333
Median Absolute Deviation (MAD)0
Skewness4.08337115
Sum2313
Variance0.0483737657
MonotonicityNot monotonic
2023-06-29T19:28:40.331529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 43066
94.9%
1 2313
 
5.1%
ValueCountFrequency (%)
0 43066
94.9%
1 2313
 
5.1%
ValueCountFrequency (%)
1 2313
 
5.1%
0 43066
94.9%

Adventure
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0769959673
Minimum0
Maximum1
Zeros41885
Zeros (%)92.3%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:40.423493image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2665879863
Coefficient of variation (CV)3.462362974
Kurtosis8.072133676
Mean0.0769959673
Median Absolute Deviation (MAD)0
Skewness3.173606452
Sum3494
Variance0.07106915444
MonotonicityNot monotonic
2023-06-29T19:28:40.516494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 41885
92.3%
1 3494
 
7.7%
ValueCountFrequency (%)
0 41885
92.3%
1 3494
 
7.7%
ValueCountFrequency (%)
1 3494
 
7.7%
0 41885
92.3%

Family
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06099737764
Minimum0
Maximum1
Zeros42611
Zeros (%)93.9%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:40.607497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2393281425
Coefficient of variation (CV)3.923580844
Kurtosis11.46050208
Mean0.06099737764
Median Absolute Deviation (MAD)0
Skewness3.668786854
Sum2768
Variance0.05727795978
MonotonicityNot monotonic
2023-06-29T19:28:40.706517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 42611
93.9%
1 2768
 
6.1%
ValueCountFrequency (%)
0 42611
93.9%
1 2768
 
6.1%
ValueCountFrequency (%)
1 2768
 
6.1%
0 42611
93.9%

Comedy
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2904647524
Minimum0
Maximum1
Zeros32198
Zeros (%)71.0%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:40.807494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4539818518
Coefficient of variation (CV)1.562949886
Kurtosis-1.147862485
Mean0.2904647524
Median Absolute Deviation (MAD)0
Skewness0.9231403505
Sum13181
Variance0.2060995218
MonotonicityNot monotonic
2023-06-29T19:28:40.903526image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 32198
71.0%
1 13181
29.0%
ValueCountFrequency (%)
0 32198
71.0%
1 13181
29.0%
ValueCountFrequency (%)
1 13181
29.0%
0 32198
71.0%

Animation
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04259679587
Minimum0
Maximum1
Zeros43446
Zeros (%)95.7%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:41.011494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2019485271
Coefficient of variation (CV)4.740932338
Kurtosis18.52260917
Mean0.04259679587
Median Absolute Deviation (MAD)0
Skewness4.530098545
Sum1933
Variance0.04078320758
MonotonicityNot monotonic
2023-06-29T19:28:41.099524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 43446
95.7%
1 1933
 
4.3%
ValueCountFrequency (%)
0 43446
95.7%
1 1933
 
4.3%
ValueCountFrequency (%)
1 1933
 
4.3%
0 43446
95.7%

genres
Text

Distinct4066
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:41.231524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length264
Median length225
Mean length62.89292404
Min length2

Characters and Unicode

Total characters2854018
Distinct characters46
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2365 ?
Unique (%)5.2%

Sample

1st row[{'id': 16, 'name': 'Animation'}, {'id': 35, 'name': 'Comedy'}, {'id': 10751, 'name': 'Family'}]
2nd row[{'id': 12, 'name': 'Adventure'}, {'id': 14, 'name': 'Fantasy'}, {'id': 10751, 'name': 'Family'}]
3rd row[{'id': 10749, 'name': 'Romance'}, {'id': 35, 'name': 'Comedy'}]
4th row[{'id': 35, 'name': 'Comedy'}, {'id': 18, 'name': 'Drama'}, {'id': 10749, 'name': 'Romance'}]
5th row[{'id': 35, 'name': 'Comedy'}]
ValueCountFrequency (%)
id 91045
24.6%
name 91045
24.6%
drama 20256
 
5.5%
18 20256
 
5.5%
35 13181
 
3.6%
comedy 13181
 
3.6%
53 7620
 
2.1%
thriller 7620
 
2.1%
10749 6733
 
1.8%
romance 6733
 
1.8%
Other values (35) 92705
25.0%
2023-06-29T19:28:41.537493image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 546270
19.1%
324996
 
11.4%
: 182090
 
6.4%
a 152861
 
5.4%
e 146817
 
5.1%
m 144142
 
5.1%
, 139095
 
4.9%
i 130713
 
4.6%
n 126717
 
4.4%
d 107720
 
3.8%
Other values (36) 852597
29.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1058604
37.1%
Other Punctuation 867455
30.4%
Space Separator 324996
 
11.4%
Decimal Number 234492
 
8.2%
Close Punctuation 136424
 
4.8%
Open Punctuation 136424
 
4.8%
Uppercase Letter 95623
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 152861
14.4%
e 146817
13.9%
m 144142
13.6%
i 130713
12.3%
n 126717
12.0%
d 107720
10.2%
r 69076
6.5%
o 48533
 
4.6%
y 28508
 
2.7%
c 27978
 
2.6%
Other values (7) 75539
7.1%
Uppercase Letter
ValueCountFrequency (%)
D 24177
25.3%
C 17486
18.3%
A 12021
12.6%
F 9746
10.2%
T 8387
 
8.8%
R 6733
 
7.0%
H 6068
 
6.3%
M 4829
 
5.1%
S 3044
 
3.2%
W 2365
 
2.5%
Decimal Number
ValueCountFrequency (%)
1 45574
19.4%
8 39707
16.9%
5 24892
10.6%
3 23240
9.9%
7 22736
9.7%
0 21480
9.2%
9 18660
8.0%
2 17680
 
7.5%
4 13108
 
5.6%
6 7415
 
3.2%
Other Punctuation
ValueCountFrequency (%)
' 546270
63.0%
: 182090
 
21.0%
, 139095
 
16.0%
Close Punctuation
ValueCountFrequency (%)
} 91045
66.7%
] 45379
33.3%
Open Punctuation
ValueCountFrequency (%)
{ 91045
66.7%
[ 45379
33.3%
Space Separator
ValueCountFrequency (%)
324996
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1699791
59.6%
Latin 1154227
40.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 152861
13.2%
e 146817
12.7%
m 144142
12.5%
i 130713
11.3%
n 126717
11.0%
d 107720
9.3%
r 69076
6.0%
o 48533
 
4.2%
y 28508
 
2.5%
c 27978
 
2.4%
Other values (18) 171162
14.8%
Common
ValueCountFrequency (%)
' 546270
32.1%
324996
19.1%
: 182090
 
10.7%
, 139095
 
8.2%
} 91045
 
5.4%
{ 91045
 
5.4%
1 45574
 
2.7%
] 45379
 
2.7%
[ 45379
 
2.7%
8 39707
 
2.3%
Other values (8) 149211
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2854018
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 546270
19.1%
324996
 
11.4%
: 182090
 
6.4%
a 152861
 
5.4%
e 146817
 
5.1%
m 144142
 
5.1%
, 139095
 
4.9%
i 130713
 
4.6%
n 126717
 
4.4%
d 107720
 
3.8%
Other values (36) 852597
29.9%

id
Real number (ℝ)

Distinct45349
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108029.979
Minimum2
Maximum469172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:41.677494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5351.3
Q126386.5
median59859
Q3156538
95-th percentile357170.8
Maximum469172
Range469170
Interquartile range (IQR)130151.5

Descriptive statistics

Standard deviation112166.7138
Coefficient of variation (CV)1.038292471
Kurtosis0.5594153218
Mean108029.979
Median Absolute Deviation (MAD)44419
Skewness1.283008053
Sum4902292415
Variance1.258137168 × 1010
MonotonicityNot monotonic
2023-06-29T19:28:41.806495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
141971 3
 
< 0.1%
23305 2
 
< 0.1%
168538 2
 
< 0.1%
109962 2
 
< 0.1%
119916 2
 
< 0.1%
97995 2
 
< 0.1%
159849 2
 
< 0.1%
84198 2
 
< 0.1%
132641 2
 
< 0.1%
99080 2
 
< 0.1%
Other values (45339) 45358
> 99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
469172 1
< 0.1%
468707 1
< 0.1%
468343 1
< 0.1%
467731 1
< 0.1%
465044 1
< 0.1%
Distinct89
Distinct (%)0.2%
Missing11
Missing (%)< 0.1%
Memory size354.6 KiB
2023-06-29T19:28:41.938525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters90736
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)< 0.1%

Sample

1st rowen
2nd rowen
3rd rowen
4th rowen
5th rowen
ValueCountFrequency (%)
en 32204
71.0%
fr 2437
 
5.4%
it 1528
 
3.4%
ja 1350
 
3.0%
de 1078
 
2.4%
es 992
 
2.2%
ru 822
 
1.8%
hi 508
 
1.1%
ko 444
 
1.0%
zh 408
 
0.9%
Other values (79) 3597
 
7.9%
2023-06-29T19:28:42.180524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 34529
38.1%
n 32912
36.3%
r 3630
 
4.0%
f 2835
 
3.1%
i 2388
 
2.6%
t 2250
 
2.5%
a 1840
 
2.0%
s 1652
 
1.8%
j 1351
 
1.5%
d 1323
 
1.5%
Other values (16) 6026
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 90736
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 34529
38.1%
n 32912
36.3%
r 3630
 
4.0%
f 2835
 
3.1%
i 2388
 
2.6%
t 2250
 
2.5%
a 1840
 
2.0%
s 1652
 
1.8%
j 1351
 
1.5%
d 1323
 
1.5%
Other values (16) 6026
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 90736
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 34529
38.1%
n 32912
36.3%
r 3630
 
4.0%
f 2835
 
3.1%
i 2388
 
2.6%
t 2250
 
2.5%
a 1840
 
2.0%
s 1652
 
1.8%
j 1351
 
1.5%
d 1323
 
1.5%
Other values (16) 6026
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 34529
38.1%
n 32912
36.3%
r 3630
 
4.0%
f 2835
 
3.1%
i 2388
 
2.6%
t 2250
 
2.5%
a 1840
 
2.0%
s 1652
 
1.8%
j 1351
 
1.5%
d 1323
 
1.5%
Other values (16) 6026
 
6.6%

overview
Text

MISSING 

Distinct44235
Distinct (%)99.5%
Missing941
Missing (%)2.1%
Memory size354.6 KiB
2023-06-29T19:28:42.502525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1000
Median length786
Mean length323.2921374
Min length1

Characters and Unicode

Total characters14366456
Distinct characters429
Distinct categories25 ?
Distinct scripts13 ?
Distinct blocks21 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44176 ?
Unique (%)99.4%

Sample

1st rowLed by Woody, Andy's toys live happily in his room until Andy's birthday brings Buzz Lightyear onto the scene. Afraid of losing his place in Andy's heart, Woody plots against Buzz. But when circumstances separate Buzz and Woody from their owner, the duo eventually learns to put aside their differences.
2nd rowWhen siblings Judy and Peter discover an enchanted board game that opens the door to a magical world, they unwittingly invite Alan -- an adult who's been trapped inside the game for 26 years -- into their living room. Alan's only hope for freedom is to finish the game, which proves risky as all three find themselves running from giant rhinoceroses, evil monkeys and other terrifying creatures.
3rd rowA family wedding reignites the ancient feud between next-door neighbors and fishing buddies John and Max. Meanwhile, a sultry Italian divorcée opens a restaurant at the local bait shop, alarming the locals who worry she'll scare the fish away. But she's less interested in seafood than she is in cooking up a hot time with Max.
4th rowCheated on, mistreated and stepped on, the women are holding their breath, waiting for the elusive "good man" to break a string of less-than-stellar lovers. Friends and confidants Vannah, Bernie, Glo and Robin talk it all out, determined to find a better way to breathe.
5th rowJust when George Banks has recovered from his daughter's wedding, he receives the news that she's pregnant ... and that George's wife, Nina, is expecting too. He was planning on selling their home, but that's a plan that -- like George -- will have to change with the arrival of both a grandchild and a kid of his own.
ValueCountFrequency (%)
the 138089
 
5.6%
a 98898
 
4.0%
and 75263
 
3.1%
to 73327
 
3.0%
of 69578
 
2.8%
in 48145
 
2.0%
is 36502
 
1.5%
his 36165
 
1.5%
with 23904
 
1.0%
her 21485
 
0.9%
Other values (97093) 1827488
74.6%
2023-06-29T19:28:42.983525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2406483
16.8%
e 1363851
 
9.5%
a 940546
 
6.5%
t 934830
 
6.5%
i 851558
 
5.9%
o 829919
 
5.8%
n 822640
 
5.7%
s 767891
 
5.3%
r 744333
 
5.2%
h 600843
 
4.2%
Other values (419) 4103562
28.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11150647
77.6%
Space Separator 2406521
 
16.8%
Uppercase Letter 390984
 
2.7%
Other Punctuation 312833
 
2.2%
Decimal Number 42223
 
0.3%
Dash Punctuation 36768
 
0.3%
Close Punctuation 10100
 
0.1%
Open Punctuation 10077
 
0.1%
Final Punctuation 4556
 
< 0.1%
Initial Punctuation 882
 
< 0.1%
Other values (15) 865
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1363851
12.2%
a 940546
 
8.4%
t 934830
 
8.4%
i 851558
 
7.6%
o 829919
 
7.4%
n 822640
 
7.4%
s 767891
 
6.9%
r 744333
 
6.7%
h 600843
 
5.4%
l 478832
 
4.3%
Other values (142) 2815404
25.2%
Uppercase Letter
ValueCountFrequency (%)
A 42754
 
10.9%
T 35969
 
9.2%
S 31129
 
8.0%
M 23955
 
6.1%
B 23703
 
6.1%
C 22804
 
5.8%
H 19429
 
5.0%
W 18653
 
4.8%
I 16799
 
4.3%
D 16311
 
4.2%
Other values (77) 139478
35.7%
Other Letter
ValueCountFrequency (%)
6
 
4.8%
6
 
4.8%
5
 
4.0%
4
 
3.2%
3
 
2.4%
3
 
2.4%
3
 
2.4%
3
 
2.4%
2
 
1.6%
م 2
 
1.6%
Other values (76) 88
70.4%
Other Punctuation
ValueCountFrequency (%)
, 133443
42.7%
. 124802
39.9%
' 31122
 
9.9%
" 11661
 
3.7%
: 3299
 
1.1%
? 2759
 
0.9%
; 2493
 
0.8%
! 1543
 
0.5%
/ 765
 
0.2%
& 453
 
0.1%
Other values (12) 493
 
0.2%
Nonspacing Mark
ValueCountFrequency (%)
́ 4
12.1%
ి 4
12.1%
3
9.1%
3
9.1%
3
9.1%
̈ 3
9.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
2
 
6.1%
Other values (4) 5
15.2%
Decimal Number
ValueCountFrequency (%)
1 9748
23.1%
0 8265
19.6%
9 6405
15.2%
2 4251
10.1%
5 2440
 
5.8%
8 2379
 
5.6%
3 2342
 
5.5%
4 2176
 
5.2%
7 2131
 
5.0%
6 2086
 
4.9%
Spacing Mark
ValueCountFrequency (%)
11
40.7%
4
 
14.8%
3
 
11.1%
3
 
11.1%
ि 2
 
7.4%
2
 
7.4%
1
 
3.7%
ி 1
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 35245
95.9%
881
 
2.4%
633
 
1.7%
5
 
< 0.1%
4
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
® 45
70.3%
14
 
21.9%
¦ 2
 
3.1%
° 2
 
3.1%
1
 
1.6%
Math Symbol
ValueCountFrequency (%)
~ 20
50.0%
+ 11
27.5%
= 6
 
15.0%
| 2
 
5.0%
1
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 10024
99.5%
[ 50
 
0.5%
{ 2
 
< 0.1%
1
 
< 0.1%
Currency Symbol
ValueCountFrequency (%)
$ 317
96.4%
£ 10
 
3.0%
1
 
0.3%
1
 
0.3%
Space Separator
ValueCountFrequency (%)
2406483
> 99.9%
  36
 
< 0.1%
  2
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 10048
99.5%
] 50
 
0.5%
} 2
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
3847
84.4%
690
 
15.1%
» 19
 
0.4%
Initial Punctuation
ValueCountFrequency (%)
672
76.2%
192
 
21.8%
« 18
 
2.0%
Control
ValueCountFrequency (%)
106
96.4%
’ 3
 
2.7%
 1
 
0.9%
Modifier Symbol
ValueCountFrequency (%)
´ 25
65.8%
` 12
31.6%
¯ 1
 
2.6%
Format
ValueCountFrequency (%)
31
60.8%
­ 20
39.2%
Other Number
ValueCountFrequency (%)
½ 8
50.0%
¹ 8
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 19
100.0%
Line Separator
ValueCountFrequency (%)
7
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Paragraph Separator
ValueCountFrequency (%)
2
100.0%
Modifier Letter
ValueCountFrequency (%)
ʼ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11536399
80.3%
Common 2824638
 
19.7%
Cyrillic 4587
 
< 0.1%
Greek 648
 
< 0.1%
Devanagari 77
 
< 0.1%
Telugu 30
 
< 0.1%
Hiragana 20
 
< 0.1%
Tamil 19
 
< 0.1%
Han 10
 
< 0.1%
Hangul 9
 
< 0.1%
Other values (3) 19
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1363851
11.8%
a 940546
 
8.2%
t 934830
 
8.1%
i 851558
 
7.4%
o 829919
 
7.2%
n 822640
 
7.1%
s 767891
 
6.7%
r 744333
 
6.5%
h 600843
 
5.2%
l 478832
 
4.2%
Other values (132) 3201156
27.7%
Common
ValueCountFrequency (%)
2406483
85.2%
, 133443
 
4.7%
. 124802
 
4.4%
- 35245
 
1.2%
' 31122
 
1.1%
" 11661
 
0.4%
) 10048
 
0.4%
( 10024
 
0.4%
1 9748
 
0.3%
0 8265
 
0.3%
Other values (71) 43797
 
1.6%
Cyrillic
ValueCountFrequency (%)
о 470
 
10.2%
е 404
 
8.8%
а 373
 
8.1%
н 323
 
7.0%
и 299
 
6.5%
т 265
 
5.8%
р 240
 
5.2%
с 218
 
4.8%
в 173
 
3.8%
л 161
 
3.5%
Other values (46) 1661
36.2%
Greek
ValueCountFrequency (%)
α 60
 
9.3%
ο 55
 
8.5%
τ 43
 
6.6%
ι 36
 
5.6%
η 36
 
5.6%
ν 34
 
5.2%
ε 31
 
4.8%
ρ 31
 
4.8%
π 30
 
4.6%
ς 30
 
4.6%
Other values (33) 262
40.4%
Devanagari
ValueCountFrequency (%)
11
 
14.3%
6
 
7.8%
6
 
7.8%
5
 
6.5%
4
 
5.2%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
Other values (21) 30
39.0%
Hiragana
ValueCountFrequency (%)
4
20.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (7) 7
35.0%
Telugu
ValueCountFrequency (%)
ి 4
13.3%
3
10.0%
3
10.0%
3
10.0%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
1
 
3.3%
Other values (6) 6
20.0%
Tamil
ValueCountFrequency (%)
3
15.8%
2
10.5%
2
10.5%
2
10.5%
2
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (3) 3
15.8%
Han
ValueCountFrequency (%)
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Hangul
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Thai
ValueCountFrequency (%)
2
25.0%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Arabic
ValueCountFrequency (%)
م 2
50.0%
ہ 1
25.0%
ت 1
25.0%
Inherited
ValueCountFrequency (%)
́ 4
57.1%
̈ 3
42.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14348456
99.9%
Punctuation 7270
 
0.1%
None 5932
 
< 0.1%
Cyrillic 4587
 
< 0.1%
Devanagari 77
 
< 0.1%
Telugu 30
 
< 0.1%
Hiragana 20
 
< 0.1%
Tamil 19
 
< 0.1%
Letterlike Symbols 14
 
< 0.1%
CJK 10
 
< 0.1%
Other values (11) 41
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2406483
16.8%
e 1363851
 
9.5%
a 940546
 
6.6%
t 934830
 
6.5%
i 851558
 
5.9%
o 829919
 
5.8%
n 822640
 
5.7%
s 767891
 
5.4%
r 744333
 
5.2%
h 600843
 
4.2%
Other values (82) 4085562
28.5%
Punctuation
ValueCountFrequency (%)
3847
52.9%
881
 
12.1%
690
 
9.5%
672
 
9.2%
633
 
8.7%
303
 
4.2%
192
 
2.6%
31
 
0.4%
7
 
0.1%
5
 
0.1%
Other values (4) 9
 
0.1%
None
ValueCountFrequency (%)
é 1552
26.2%
ä 294
 
5.0%
á 293
 
4.9%
ö 250
 
4.2%
í 243
 
4.1%
è 209
 
3.5%
ü 178
 
3.0%
ı 165
 
2.8%
ó 164
 
2.8%
ç 158
 
2.7%
Other values (141) 2426
40.9%
Cyrillic
ValueCountFrequency (%)
о 470
 
10.2%
е 404
 
8.8%
а 373
 
8.1%
н 323
 
7.0%
и 299
 
6.5%
т 265
 
5.8%
р 240
 
5.2%
с 218
 
4.8%
в 173
 
3.8%
л 161
 
3.5%
Other values (46) 1661
36.2%
Letterlike Symbols
ValueCountFrequency (%)
14
100.0%
Devanagari
ValueCountFrequency (%)
11
 
14.3%
6
 
7.8%
6
 
7.8%
5
 
6.5%
4
 
5.2%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
3
 
3.9%
Other values (21) 30
39.0%
Alphabetic PF
ValueCountFrequency (%)
4
100.0%
Hiragana
ValueCountFrequency (%)
4
20.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
1
 
5.0%
Other values (7) 7
35.0%
Diacriticals
ValueCountFrequency (%)
́ 4
57.1%
̈ 3
42.9%
Telugu
ValueCountFrequency (%)
ి 4
13.3%
3
10.0%
3
10.0%
3
10.0%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
2
 
6.7%
1
 
3.3%
Other values (6) 6
20.0%
Tamil
ValueCountFrequency (%)
3
15.8%
2
10.5%
2
10.5%
2
10.5%
2
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Other values (3) 3
15.8%
Arabic
ValueCountFrequency (%)
م 2
50.0%
ہ 1
25.0%
ت 1
25.0%
Hangul
ValueCountFrequency (%)
2
22.2%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
Number Forms
ValueCountFrequency (%)
2
100.0%
Modifier Letters
ValueCountFrequency (%)
ʼ 2
100.0%
Thai
ValueCountFrequency (%)
2
25.0%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
CJK
ValueCountFrequency (%)
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Math Operators
ValueCountFrequency (%)
1
100.0%
Katakana
ValueCountFrequency (%)
1
100.0%
Currency Symbols
ValueCountFrequency (%)
1
50.0%
1
50.0%
Specials
ValueCountFrequency (%)
1
100.0%

popularity
Real number (ℝ)

SKEWED 

Distinct43734
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.926356276
Minimum0
Maximum547.488298
Zeros40
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:43.125523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0208069
Q10.388835
median1.130503
Q33.6906865
95-th percentile11.063588
Maximum547.488298
Range547.488298
Interquartile range (IQR)3.3018515

Descriptive statistics

Standard deviation6.009491011
Coefficient of variation (CV)2.053574631
Kurtosis1923.794721
Mean2.926356276
Median Absolute Deviation (MAD)0.967653
Skewness29.21581948
Sum132795.1215
Variance36.11398221
MonotonicityNot monotonic
2023-06-29T19:28:43.248524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 × 10-656
 
0.1%
0.000308 42
 
0.1%
0 40
 
0.1%
0.00022 39
 
0.1%
0.000578 38
 
0.1%
0.001177 38
 
0.1%
0.000844 38
 
0.1%
0.002001 27
 
0.1%
0.003013 21
 
< 0.1%
0.00353 19
 
< 0.1%
Other values (43724) 45021
99.2%
ValueCountFrequency (%)
0 40
0.1%
1 × 10-656
0.1%
2 × 10-66
 
< 0.1%
3 × 10-66
 
< 0.1%
4 × 10-65
 
< 0.1%
ValueCountFrequency (%)
547.488298 1
< 0.1%
294.337037 1
< 0.1%
287.253654 1
< 0.1%
228.032744 1
< 0.1%
213.849907 1
< 0.1%
Distinct22706
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:43.513527image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1252
Median length954
Mean length70.22193085
Min length2

Characters and Unicode

Total characters3186601
Distinct characters293
Distinct categories15 ?
Distinct scripts6 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20344 ?
Unique (%)44.8%

Sample

1st row[{'name': 'Pixar Animation Studios', 'id': 3}]
2nd row[{'name': 'TriStar Pictures', 'id': 559}, {'name': 'Teitler Film', 'id': 2550}, {'name': 'Interscope Communications', 'id': 10201}]
3rd row[{'name': 'Warner Bros.', 'id': 6194}, {'name': 'Lancaster Gate', 'id': 19464}]
4th row[{'name': 'Twentieth Century Fox Film Corporation', 'id': 306}]
5th row[{'name': 'Sandollar Productions', 'id': 5842}, {'name': 'Touchstone Pictures', 'id': 9195}]
ValueCountFrequency (%)
name 70543
 
17.6%
id 70543
 
17.6%
12640
 
3.2%
films 9455
 
2.4%
pictures 9267
 
2.3%
productions 9062
 
2.3%
film 6680
 
1.7%
entertainment 5155
 
1.3%
corporation 2189
 
0.5%
company 1769
 
0.4%
Other values (42189) 203823
50.8%
2023-06-29T19:28:43.949524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 422849
 
13.3%
355760
 
11.2%
i 177494
 
5.6%
e 165206
 
5.2%
n 160523
 
5.0%
a 147699
 
4.6%
: 141093
 
4.4%
m 114823
 
3.6%
, 107905
 
3.4%
d 104017
 
3.3%
Other values (283) 1289232
40.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1410442
44.3%
Other Punctuation 679997
21.3%
Space Separator 355760
 
11.2%
Decimal Number 295733
 
9.3%
Uppercase Letter 198999
 
6.2%
Open Punctuation 120249
 
3.8%
Close Punctuation 120248
 
3.8%
Dash Punctuation 4331
 
0.1%
Math Symbol 662
 
< 0.1%
Other Letter 140
 
< 0.1%
Other values (5) 40
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 177494
12.6%
e 165206
11.7%
n 160523
11.4%
a 147699
10.5%
m 114823
8.1%
d 104017
7.4%
o 85308
 
6.0%
r 83559
 
5.9%
t 83450
 
5.9%
s 62678
 
4.4%
Other values (102) 225685
16.0%
Other Letter
ValueCountFrequency (%)
9
 
6.4%
8
 
5.7%
6
 
4.3%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
5
 
3.6%
4
 
2.9%
3
 
2.1%
Other values (62) 85
60.7%
Uppercase Letter
ValueCountFrequency (%)
P 27885
14.0%
F 26364
13.2%
C 20588
 
10.3%
M 13363
 
6.7%
S 11915
 
6.0%
E 9747
 
4.9%
A 9549
 
4.8%
T 9360
 
4.7%
B 9002
 
4.5%
G 7813
 
3.9%
Other values (52) 53413
26.8%
Other Punctuation
ValueCountFrequency (%)
' 422849
62.2%
: 141093
 
20.7%
, 107905
 
15.9%
. 5671
 
0.8%
" 987
 
0.1%
& 764
 
0.1%
/ 645
 
0.1%
! 36
 
< 0.1%
% 18
 
< 0.1%
\ 12
 
< 0.1%
Other values (6) 17
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 45080
15.2%
2 33554
11.3%
3 31848
10.8%
4 30679
10.4%
6 28097
9.5%
5 27812
9.4%
8 25847
8.7%
7 24559
8.3%
9 24359
8.2%
0 23898
8.1%
Open Punctuation
ValueCountFrequency (%)
{ 70542
58.7%
[ 45388
37.7%
( 4318
 
3.6%
1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
} 70542
58.7%
] 45388
37.7%
) 4317
 
3.6%
1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 4329
> 99.9%
2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 661
99.8%
| 1
 
0.2%
Other Symbol
ValueCountFrequency (%)
° 23
92.0%
2
 
8.0%
Final Punctuation
ValueCountFrequency (%)
» 3
50.0%
3
50.0%
Other Number
ValueCountFrequency (%)
² 1
50.0%
½ 1
50.0%
Space Separator
ValueCountFrequency (%)
355760
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1609038
50.5%
Common 1577018
49.5%
Cyrillic 373
 
< 0.1%
Hangul 115
 
< 0.1%
Greek 31
 
< 0.1%
Han 26
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 177494
11.0%
e 165206
 
10.3%
n 160523
 
10.0%
a 147699
 
9.2%
m 114823
 
7.1%
d 104017
 
6.5%
o 85308
 
5.3%
r 83559
 
5.2%
t 83450
 
5.2%
s 62678
 
3.9%
Other values (99) 424281
26.4%
Hangul
ValueCountFrequency (%)
9
 
7.8%
8
 
7.0%
6
 
5.2%
5
 
4.3%
5
 
4.3%
5
 
4.3%
5
 
4.3%
5
 
4.3%
4
 
3.5%
3
 
2.6%
Other values (43) 60
52.2%
Common
ValueCountFrequency (%)
' 422849
26.8%
355760
22.6%
: 141093
 
8.9%
, 107905
 
6.8%
{ 70542
 
4.5%
} 70542
 
4.5%
[ 45388
 
2.9%
] 45388
 
2.9%
1 45080
 
2.9%
2 33554
 
2.1%
Other values (36) 238917
15.1%
Cyrillic
ValueCountFrequency (%)
и 34
 
9.1%
о 28
 
7.5%
а 26
 
7.0%
л 22
 
5.9%
н 20
 
5.4%
м 19
 
5.1%
т 17
 
4.6%
с 16
 
4.3%
е 16
 
4.3%
ь 16
 
4.3%
Other values (36) 159
42.6%
Greek
ValueCountFrequency (%)
ο 3
 
9.7%
ν 3
 
9.7%
τ 2
 
6.5%
ρ 2
 
6.5%
ι 2
 
6.5%
η 2
 
6.5%
λ 2
 
6.5%
Ε 2
 
6.5%
Κ 2
 
6.5%
α 1
 
3.2%
Other values (10) 10
32.3%
Han
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (9) 9
34.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3180377
99.8%
None 5706
 
0.2%
Cyrillic 373
 
< 0.1%
Hangul 113
 
< 0.1%
CJK 26
 
< 0.1%
Punctuation 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 422849
 
13.3%
355760
 
11.2%
i 177494
 
5.6%
e 165206
 
5.2%
n 160523
 
5.0%
a 147699
 
4.6%
: 141093
 
4.4%
m 114823
 
3.6%
, 107905
 
3.4%
d 104017
 
3.3%
Other values (78) 1283008
40.3%
None
ValueCountFrequency (%)
é 3176
55.7%
ó 416
 
7.3%
á 317
 
5.6%
í 173
 
3.0%
ü 154
 
2.7%
ñ 150
 
2.6%
ô 140
 
2.5%
ä 137
 
2.4%
è 136
 
2.4%
ö 132
 
2.3%
Other values (75) 775
 
13.6%
Cyrillic
ValueCountFrequency (%)
и 34
 
9.1%
о 28
 
7.5%
а 26
 
7.0%
л 22
 
5.9%
н 20
 
5.4%
м 19
 
5.1%
т 17
 
4.6%
с 16
 
4.3%
е 16
 
4.3%
ь 16
 
4.3%
Other values (36) 159
42.6%
Hangul
ValueCountFrequency (%)
9
 
8.0%
8
 
7.1%
6
 
5.3%
5
 
4.4%
5
 
4.4%
5
 
4.4%
5
 
4.4%
5
 
4.4%
4
 
3.5%
3
 
2.7%
Other values (42) 58
51.3%
Punctuation
ValueCountFrequency (%)
3
50.0%
2
33.3%
1
 
16.7%
CJK
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (9) 9
34.6%
Distinct2390
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:44.215494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1039
Median length649
Mean length53.28682871
Min length2

Characters and Unicode

Total characters2418103
Distinct characters65
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1765 ?
Unique (%)3.9%

Sample

1st row[{'iso_3166_1': 'US', 'name': 'United States of America'}]
2nd row[{'iso_3166_1': 'US', 'name': 'United States of America'}]
3rd row[{'iso_3166_1': 'US', 'name': 'United States of America'}]
4th row[{'iso_3166_1': 'US', 'name': 'United States of America'}]
5th row[{'iso_3166_1': 'US', 'name': 'United States of America'}]
ValueCountFrequency (%)
iso_3166_1 49415
18.1%
name 49415
18.1%
united 25269
9.2%
states 21150
7.7%
of 21149
7.7%
america 21149
7.7%
us 21149
7.7%
6211
 
2.3%
gb 4092
 
1.5%
kingdom 4092
 
1.5%
Other values (341) 50133
18.3%
2023-06-29T19:28:44.634524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 395315
16.3%
227845
 
9.4%
e 130072
 
5.4%
a 119915
 
5.0%
i 107969
 
4.5%
_ 98830
 
4.1%
1 98830
 
4.1%
6 98830
 
4.1%
: 98830
 
4.1%
n 96917
 
4.0%
Other values (55) 944750
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 904537
37.4%
Other Punctuation 553817
22.9%
Decimal Number 247075
 
10.2%
Space Separator 227845
 
9.4%
Uppercase Letter 196411
 
8.1%
Connector Punctuation 98830
 
4.1%
Close Punctuation 94794
 
3.9%
Open Punctuation 94794
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 130072
14.4%
a 119915
13.3%
i 107969
11.9%
n 96917
10.7%
o 78999
8.7%
m 78123
8.6%
s 74105
8.2%
t 72626
8.0%
d 34551
 
3.8%
r 32493
 
3.6%
Other values (16) 78767
8.7%
Uppercase Letter
ValueCountFrequency (%)
U 48397
24.6%
S 46881
23.9%
A 25529
13.0%
F 8676
 
4.4%
R 7993
 
4.1%
I 7595
 
3.9%
G 6922
 
3.5%
K 6808
 
3.5%
B 5858
 
3.0%
C 5371
 
2.7%
Other values (16) 26381
13.4%
Other Punctuation
ValueCountFrequency (%)
' 395315
71.4%
: 98830
 
17.8%
, 59662
 
10.8%
" 10
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 98830
40.0%
6 98830
40.0%
3 49415
20.0%
Close Punctuation
ValueCountFrequency (%)
} 49415
52.1%
] 45379
47.9%
Open Punctuation
ValueCountFrequency (%)
{ 49415
52.1%
[ 45379
47.9%
Space Separator
ValueCountFrequency (%)
227845
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 98830
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1317155
54.5%
Latin 1100948
45.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 130072
11.8%
a 119915
10.9%
i 107969
9.8%
n 96917
 
8.8%
o 78999
 
7.2%
m 78123
 
7.1%
s 74105
 
6.7%
t 72626
 
6.6%
U 48397
 
4.4%
S 46881
 
4.3%
Other values (42) 246944
22.4%
Common
ValueCountFrequency (%)
' 395315
30.0%
227845
17.3%
_ 98830
 
7.5%
1 98830
 
7.5%
6 98830
 
7.5%
: 98830
 
7.5%
, 59662
 
4.5%
} 49415
 
3.8%
{ 49415
 
3.8%
3 49415
 
3.8%
Other values (3) 90768
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2418103
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 395315
16.3%
227845
 
9.4%
e 130072
 
5.4%
a 119915
 
5.0%
i 107969
 
4.5%
_ 98830
 
4.1%
1 98830
 
4.1%
6 98830
 
4.1%
: 98830
 
4.1%
n 96917
 
4.0%
Other values (55) 944750
39.1%
Distinct17334
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:45.038523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters453790
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8571 ?
Unique (%)18.9%

Sample

1st row1995-10-30
2nd row1995-12-15
3rd row1995-12-22
4th row1995-12-22
5th row1995-02-10
ValueCountFrequency (%)
2008-01-01 136
 
0.3%
2009-01-01 121
 
0.3%
2007-01-01 118
 
0.3%
2005-01-01 111
 
0.2%
2006-01-01 101
 
0.2%
2002-01-01 96
 
0.2%
2004-01-01 90
 
0.2%
2001-01-01 84
 
0.2%
2003-01-01 76
 
0.2%
1997-01-01 69
 
0.2%
Other values (17324) 44377
97.8%
2023-06-29T19:28:45.365524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 97607
21.5%
- 90758
20.0%
1 84059
18.5%
2 52808
11.6%
9 39777
8.8%
3 15435
 
3.4%
8 15280
 
3.4%
6 15021
 
3.3%
5 14836
 
3.3%
7 14290
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 363032
80.0%
Dash Punctuation 90758
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 97607
26.9%
1 84059
23.2%
2 52808
14.5%
9 39777
11.0%
3 15435
 
4.3%
8 15280
 
4.2%
6 15021
 
4.1%
5 14836
 
4.1%
7 14290
 
3.9%
4 13919
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 90758
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 453790
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 97607
21.5%
- 90758
20.0%
1 84059
18.5%
2 52808
11.6%
9 39777
8.8%
3 15435
 
3.4%
8 15280
 
3.4%
6 15021
 
3.3%
5 14836
 
3.3%
7 14290
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 453790
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 97607
21.5%
- 90758
20.0%
1 84059
18.5%
2 52808
11.6%
9 39777
8.8%
3 15435
 
3.4%
8 15280
 
3.4%
6 15021
 
3.3%
5 14836
 
3.3%
7 14290
 
3.1%

revenue
Real number (ℝ)

ZEROS 

Distinct6863
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11229356.85
Minimum0
Maximum2787965087
Zeros37972
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:45.513528image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile48018458.8
Maximum2787965087
Range2787965087
Interquartile range (IQR)0

Descriptive statistics

Standard deviation64387893.11
Coefficient of variation (CV)5.733889657
Kurtosis237.0928809
Mean11229356.85
Median Absolute Deviation (MAD)0
Skewness12.25512449
Sum5.095769846 × 1011
Variance4.145800779 × 1015
MonotonicityNot monotonic
2023-06-29T19:28:45.641524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37972
83.7%
12000000 20
 
< 0.1%
10000000 19
 
< 0.1%
11000000 19
 
< 0.1%
2000000 18
 
< 0.1%
6000000 17
 
< 0.1%
5000000 14
 
< 0.1%
8000000 13
 
< 0.1%
500000 13
 
< 0.1%
1 12
 
< 0.1%
Other values (6853) 7262
 
16.0%
ValueCountFrequency (%)
0 37972
83.7%
1 12
 
< 0.1%
2 3
 
< 0.1%
3 9
 
< 0.1%
4 4
 
< 0.1%
ValueCountFrequency (%)
2787965087 1
< 0.1%
2068223624 1
< 0.1%
1845034188 1
< 0.1%
1519557910 1
< 0.1%
1513528810 1
< 0.1%

runtime
Real number (ℝ)

ZEROS 

Distinct353
Distinct (%)0.8%
Missing246
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean94.1810427
Minimum0
Maximum1256
Zeros1535
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:45.772496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q185
median95
Q3107
95-th percentile138
Maximum1256
Range1256
Interquartile range (IQR)22

Descriptive statistics

Standard deviation38.34005304
Coefficient of variation (CV)0.4070888572
Kurtosis93.92956811
Mean94.1810427
Median Absolute Deviation (MAD)11
Skewness4.490833231
Sum4250673
Variance1469.959667
MonotonicityNot monotonic
2023-06-29T19:28:45.907524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 2549
 
5.6%
0 1535
 
3.4%
100 1470
 
3.2%
95 1410
 
3.1%
93 1214
 
2.7%
96 1104
 
2.4%
92 1079
 
2.4%
94 1062
 
2.3%
91 1055
 
2.3%
88 1030
 
2.3%
Other values (343) 31625
69.7%
ValueCountFrequency (%)
0 1535
3.4%
1 107
 
0.2%
2 33
 
0.1%
3 48
 
0.1%
4 50
 
0.1%
ValueCountFrequency (%)
1256 1
< 0.1%
1140 2
< 0.1%
931 1
< 0.1%
925 1
< 0.1%
900 1
< 0.1%
Distinct1931
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:46.143494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length765
Median length40
Mean length46.98891558
Min length2

Characters and Unicode

Total characters2132310
Distinct characters184
Distinct categories11 ?
Distinct scripts15 ?
Distinct blocks16 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1366 ?
Unique (%)3.0%

Sample

1st row[{'iso_639_1': 'en', 'name': 'English'}]
2nd row[{'iso_639_1': 'en', 'name': 'English'}, {'iso_639_1': 'fr', 'name': 'Français'}]
3rd row[{'iso_639_1': 'en', 'name': 'English'}]
4th row[{'iso_639_1': 'en', 'name': 'English'}]
5th row[{'iso_639_1': 'en', 'name': 'English'}]
ValueCountFrequency (%)
iso_639_1 53277
24.4%
name 53277
24.4%
english 28731
13.2%
en 28731
13.2%
4748
 
2.2%
fr 4194
 
1.9%
français 4194
 
1.9%
deutsch 2624
 
1.2%
de 2624
 
1.2%
español 2412
 
1.1%
Other values (203) 33477
15.3%
2023-06-29T19:28:46.568524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 426216
20.0%
172910
 
8.1%
n 120549
 
5.7%
_ 106554
 
5.0%
: 106554
 
5.0%
s 99179
 
4.7%
i 94078
 
4.4%
e 92705
 
4.3%
a 75201
 
3.5%
, 64943
 
3.0%
Other values (174) 773421
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 771585
36.2%
Other Punctuation 598804
28.1%
Decimal Number 213134
 
10.0%
Space Separator 172910
 
8.1%
Connector Punctuation 106554
 
5.0%
Close Punctuation 98656
 
4.6%
Open Punctuation 98656
 
4.6%
Uppercase Letter 46430
 
2.2%
Other Letter 22194
 
1.0%
Spacing Mark 1838
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 120549
15.6%
s 99179
12.9%
i 94078
12.2%
e 92705
12.0%
a 75201
9.7%
o 61230
7.9%
m 53989
7.0%
l 36035
 
4.7%
h 33815
 
4.4%
g 30514
 
4.0%
Other values (65) 74290
9.6%
Other Letter
ValueCountFrequency (%)
1759
 
7.9%
1759
 
7.9%
1759
 
7.9%
1263
 
5.7%
946
 
4.3%
790
 
3.6%
790
 
3.6%
707
 
3.2%
707
 
3.2%
707
 
3.2%
Other values (46) 11007
49.6%
Uppercase Letter
ValueCountFrequency (%)
E 31200
67.2%
F 4196
 
9.0%
D 2926
 
6.3%
P 2677
 
5.8%
I 2366
 
5.1%
N 829
 
1.8%
L 505
 
1.1%
M 362
 
0.8%
T 308
 
0.7%
Č 284
 
0.6%
Other values (13) 777
 
1.7%
Spacing Mark
ValueCountFrequency (%)
707
38.5%
ि 707
38.5%
136
 
7.4%
ி 111
 
6.0%
94
 
5.1%
47
 
2.6%
18
 
1.0%
18
 
1.0%
Other Punctuation
ValueCountFrequency (%)
' 426216
71.2%
: 106554
 
17.8%
, 64943
 
10.8%
/ 1015
 
0.2%
? 50
 
< 0.1%
\ 26
 
< 0.1%
Nonspacing Mark
ValueCountFrequency (%)
707
45.6%
ִ 430
27.8%
ְ 215
 
13.9%
111
 
7.2%
68
 
4.4%
18
 
1.2%
Decimal Number
ValueCountFrequency (%)
9 53303
25.0%
3 53277
25.0%
6 53277
25.0%
1 53277
25.0%
Close Punctuation
ValueCountFrequency (%)
} 53277
54.0%
] 45379
46.0%
Open Punctuation
ValueCountFrequency (%)
{ 53277
54.0%
[ 45379
46.0%
Space Separator
ValueCountFrequency (%)
172910
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 106554
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1288714
60.4%
Latin 805626
37.8%
Han 10485
 
0.5%
Cyrillic 10454
 
0.5%
Devanagari 4242
 
0.2%
Arabic 3344
 
0.2%
Hangul 3252
 
0.2%
Hebrew 1720
 
0.1%
Greek 1704
 
0.1%
Thai 1232
 
0.1%
Other values (5) 1537
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 120549
15.0%
s 99179
12.3%
i 94078
11.7%
e 92705
11.5%
a 75201
9.3%
o 61230
7.6%
m 53989
6.7%
l 36035
 
4.5%
h 33815
 
4.2%
E 31200
 
3.9%
Other values (52) 107645
13.4%
Cyrillic
ValueCountFrequency (%)
с 3211
30.7%
к 1734
16.6%
и 1679
16.1%
й 1615
15.4%
у 1564
15.0%
а 113
 
1.1%
р 87
 
0.8%
У 53
 
0.5%
ї 53
 
0.5%
н 53
 
0.5%
Other values (12) 292
 
2.8%
Common
ValueCountFrequency (%)
' 426216
33.1%
172910
13.4%
_ 106554
 
8.3%
: 106554
 
8.3%
, 64943
 
5.0%
9 53303
 
4.1%
} 53277
 
4.1%
{ 53277
 
4.1%
3 53277
 
4.1%
6 53277
 
4.1%
Other values (6) 145126
 
11.3%
Arabic
ValueCountFrequency (%)
ا 537
16.1%
ر 537
16.1%
ب 341
10.2%
ل 341
10.2%
ة 341
10.2%
ع 341
10.2%
ي 341
10.2%
س 141
 
4.2%
ی 141
 
4.2%
ف 141
 
4.2%
Other values (5) 142
 
4.2%
Han
ValueCountFrequency (%)
1759
16.8%
1759
16.8%
1759
16.8%
1263
12.0%
946
9.0%
790
7.5%
790
7.5%
473
 
4.5%
473
 
4.5%
广 473
 
4.5%
Hebrew
ValueCountFrequency (%)
ִ 430
25.0%
ע 215
12.5%
ת 215
12.5%
י 215
12.5%
ר 215
12.5%
ְ 215
12.5%
ב 215
12.5%
Greek
ValueCountFrequency (%)
λ 426
25.0%
ε 213
12.5%
η 213
12.5%
ν 213
12.5%
ά 213
12.5%
κ 213
12.5%
ι 213
12.5%
Georgian
ValueCountFrequency (%)
33
14.3%
33
14.3%
33
14.3%
33
14.3%
33
14.3%
33
14.3%
33
14.3%
Devanagari
ValueCountFrequency (%)
707
16.7%
707
16.7%
707
16.7%
707
16.7%
707
16.7%
ि 707
16.7%
Hangul
ValueCountFrequency (%)
542
16.7%
542
16.7%
542
16.7%
542
16.7%
542
16.7%
542
16.7%
Thai
ValueCountFrequency (%)
352
28.6%
176
14.3%
176
14.3%
176
14.3%
176
14.3%
176
14.3%
Gurmukhi
ValueCountFrequency (%)
18
16.7%
18
16.7%
18
16.7%
18
16.7%
18
16.7%
18
16.7%
Telugu
ValueCountFrequency (%)
136
33.3%
68
16.7%
68
16.7%
68
16.7%
68
16.7%
Tamil
ValueCountFrequency (%)
111
20.0%
111
20.0%
111
20.0%
111
20.0%
ி 111
20.0%
Bengali
ValueCountFrequency (%)
94
40.0%
47
20.0%
47
20.0%
47
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2085510
97.8%
CJK 10485
 
0.5%
Cyrillic 10454
 
0.5%
None 10408
 
0.5%
Devanagari 4242
 
0.2%
Arabic 3344
 
0.2%
Hangul 3252
 
0.2%
Hebrew 1720
 
0.1%
Thai 1232
 
0.1%
Tamil 555
 
< 0.1%
Other values (6) 1108
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 426216
20.4%
172910
 
8.3%
n 120549
 
5.8%
_ 106554
 
5.1%
: 106554
 
5.1%
s 99179
 
4.8%
i 94078
 
4.5%
e 92705
 
4.4%
a 75201
 
3.6%
, 64943
 
3.1%
Other values (52) 726621
34.8%
None
ValueCountFrequency (%)
ç 4441
42.7%
ñ 2412
23.2%
ê 591
 
5.7%
λ 426
 
4.1%
ý 284
 
2.7%
Č 284
 
2.7%
ü 247
 
2.4%
ε 213
 
2.0%
η 213
 
2.0%
ν 213
 
2.0%
Other values (10) 1084
 
10.4%
Cyrillic
ValueCountFrequency (%)
с 3211
30.7%
к 1734
16.6%
и 1679
16.1%
й 1615
15.4%
у 1564
15.0%
а 113
 
1.1%
р 87
 
0.8%
У 53
 
0.5%
ї 53
 
0.5%
н 53
 
0.5%
Other values (12) 292
 
2.8%
CJK
ValueCountFrequency (%)
1759
16.8%
1759
16.8%
1759
16.8%
1263
12.0%
946
9.0%
790
7.5%
790
7.5%
473
 
4.5%
473
 
4.5%
广 473
 
4.5%
Devanagari
ValueCountFrequency (%)
707
16.7%
707
16.7%
707
16.7%
707
16.7%
707
16.7%
ि 707
16.7%
Hangul
ValueCountFrequency (%)
542
16.7%
542
16.7%
542
16.7%
542
16.7%
542
16.7%
542
16.7%
Arabic
ValueCountFrequency (%)
ا 537
16.1%
ر 537
16.1%
ب 341
10.2%
ل 341
10.2%
ة 341
10.2%
ع 341
10.2%
ي 341
10.2%
س 141
 
4.2%
ی 141
 
4.2%
ف 141
 
4.2%
Other values (5) 142
 
4.2%
Hebrew
ValueCountFrequency (%)
ִ 430
25.0%
ע 215
12.5%
ת 215
12.5%
י 215
12.5%
ר 215
12.5%
ְ 215
12.5%
ב 215
12.5%
Thai
ValueCountFrequency (%)
352
28.6%
176
14.3%
176
14.3%
176
14.3%
176
14.3%
176
14.3%
Telugu
ValueCountFrequency (%)
136
33.3%
68
16.7%
68
16.7%
68
16.7%
68
16.7%
Tamil
ValueCountFrequency (%)
111
20.0%
111
20.0%
111
20.0%
111
20.0%
ி 111
20.0%
Bengali
ValueCountFrequency (%)
94
40.0%
47
20.0%
47
20.0%
47
20.0%
Latin Ext Additional
ValueCountFrequency (%)
ế 61
50.0%
61
50.0%
Georgian
ValueCountFrequency (%)
33
14.3%
33
14.3%
33
14.3%
33
14.3%
33
14.3%
33
14.3%
33
14.3%
Gurmukhi
ValueCountFrequency (%)
18
16.7%
18
16.7%
18
16.7%
18
16.7%
18
16.7%
18
16.7%
IPA Ext
ValueCountFrequency (%)
ə 4
100.0%

status
Text

Distinct6
Distinct (%)< 0.1%
Missing80
Missing (%)0.2%
Memory size354.6 KiB
2023-06-29T19:28:46.688524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length15
Median length8
Mean length8.011722113
Min length7

Characters and Unicode

Total characters362923
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowReleased
2nd rowReleased
3rd rowReleased
4th rowReleased
5th rowReleased
ValueCountFrequency (%)
released 44939
99.0%
rumored 230
 
0.5%
production 116
 
0.3%
post 97
 
0.2%
in 19
 
< 0.1%
planned 13
 
< 0.1%
canceled 1
 
< 0.1%
2023-06-29T19:28:46.915494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 135062
37.2%
d 45299
 
12.5%
R 45169
 
12.4%
s 45036
 
12.4%
l 44953
 
12.4%
a 44953
 
12.4%
o 559
 
0.2%
r 346
 
0.1%
u 346
 
0.1%
m 230
 
0.1%
Other values (8) 970
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 317392
87.5%
Uppercase Letter 45415
 
12.5%
Space Separator 116
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 135062
42.6%
d 45299
 
14.3%
s 45036
 
14.2%
l 44953
 
14.2%
a 44953
 
14.2%
o 559
 
0.2%
r 346
 
0.1%
u 346
 
0.1%
m 230
 
0.1%
t 213
 
0.1%
Other values (3) 395
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
R 45169
99.5%
P 226
 
0.5%
I 19
 
< 0.1%
C 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 362807
> 99.9%
Common 116
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 135062
37.2%
d 45299
 
12.5%
R 45169
 
12.4%
s 45036
 
12.4%
l 44953
 
12.4%
a 44953
 
12.4%
o 559
 
0.2%
r 346
 
0.1%
u 346
 
0.1%
m 230
 
0.1%
Other values (7) 854
 
0.2%
Common
ValueCountFrequency (%)
116
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 362923
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 135062
37.2%
d 45299
 
12.5%
R 45169
 
12.4%
s 45036
 
12.4%
l 44953
 
12.4%
a 44953
 
12.4%
o 559
 
0.2%
r 346
 
0.1%
u 346
 
0.1%
m 230
 
0.1%
Other values (8) 970
 
0.3%

tagline
Text

MISSING 

Distinct20270
Distinct (%)99.4%
Missing24980
Missing (%)55.0%
Memory size354.6 KiB
2023-06-29T19:28:47.165493image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length297
Median length204
Mean length46.99803912
Min length1

Characters and Unicode

Total characters958713
Distinct characters170
Distinct categories17 ?
Distinct scripts6 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20164 ?
Unique (%)98.8%

Sample

1st rowRoll the dice and unleash the excitement!
2nd rowStill Yelling. Still Fighting. Still Ready for Love.
3rd rowFriends are the people who let you be yourself... and never let you forget it.
4th rowJust When His World Is Back To Normal... He's In For The Surprise Of His Life!
5th rowA Los Angeles Crime Saga
ValueCountFrequency (%)
the 10998
 
6.3%
a 6815
 
3.9%
of 4405
 
2.5%
to 3584
 
2.1%
is 2796
 
1.6%
in 2693
 
1.5%
and 2682
 
1.5%
you 2389
 
1.4%
1582
 
0.9%
for 1523
 
0.9%
Other values (15100) 134473
77.3%
2023-06-29T19:28:47.584523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
153689
16.0%
e 94415
 
9.8%
t 57269
 
6.0%
o 56567
 
5.9%
a 51474
 
5.4%
n 47498
 
5.0%
i 46037
 
4.8%
r 44994
 
4.7%
s 42362
 
4.4%
h 37172
 
3.9%
Other values (160) 327236
34.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 680493
71.0%
Space Separator 153689
 
16.0%
Uppercase Letter 74995
 
7.8%
Other Punctuation 44585
 
4.7%
Decimal Number 2687
 
0.3%
Dash Punctuation 1944
 
0.2%
Final Punctuation 98
 
< 0.1%
Open Punctuation 56
 
< 0.1%
Close Punctuation 55
 
< 0.1%
Currency Symbol 37
 
< 0.1%
Other values (7) 74
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 94415
13.9%
t 57269
 
8.4%
o 56567
 
8.3%
a 51474
 
7.6%
n 47498
 
7.0%
i 46037
 
6.8%
r 44994
 
6.6%
s 42362
 
6.2%
h 37172
 
5.5%
l 30174
 
4.4%
Other values (43) 172531
25.4%
Other Letter
ValueCountFrequency (%)
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
1
 
2.9%
Other values (24) 24
70.6%
Uppercase Letter
ValueCountFrequency (%)
T 10009
 
13.3%
A 6874
 
9.2%
S 5652
 
7.5%
H 4402
 
5.9%
I 4387
 
5.8%
E 4306
 
5.7%
W 3681
 
4.9%
O 3478
 
4.6%
N 3195
 
4.3%
L 3194
 
4.3%
Other values (20) 25817
34.4%
Other Punctuation
ValueCountFrequency (%)
. 26647
59.8%
! 5784
 
13.0%
' 5674
 
12.7%
, 4226
 
9.5%
? 1161
 
2.6%
" 582
 
1.3%
148
 
0.3%
: 138
 
0.3%
& 83
 
0.2%
* 42
 
0.1%
Other values (7) 100
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 802
29.8%
1 516
19.2%
2 299
 
11.1%
3 208
 
7.7%
9 208
 
7.7%
5 168
 
6.3%
4 140
 
5.2%
6 121
 
4.5%
7 121
 
4.5%
8 104
 
3.9%
Math Symbol
ValueCountFrequency (%)
+ 5
35.7%
= 5
35.7%
| 2
 
14.3%
~ 1
 
7.1%
1
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 1927
99.1%
9
 
0.5%
8
 
0.4%
Final Punctuation
ValueCountFrequency (%)
82
83.7%
15
 
15.3%
» 1
 
1.0%
Initial Punctuation
ValueCountFrequency (%)
14
73.7%
4
 
21.1%
« 1
 
5.3%
Open Punctuation
ValueCountFrequency (%)
( 49
87.5%
[ 7
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 48
87.3%
] 7
 
12.7%
Other Number
ValueCountFrequency (%)
½ 2
66.7%
² 1
33.3%
Modifier Letter
ValueCountFrequency (%)
ˌ 1
50.0%
ˈ 1
50.0%
Space Separator
ValueCountFrequency (%)
153689
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 37
100.0%
Nonspacing Mark
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 755488
78.8%
Common 203190
 
21.2%
Han 21
 
< 0.1%
Tamil 5
 
< 0.1%
Hiragana 5
 
< 0.1%
Katakana 4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 94415
 
12.5%
t 57269
 
7.6%
o 56567
 
7.5%
a 51474
 
6.8%
n 47498
 
6.3%
i 46037
 
6.1%
r 44994
 
6.0%
s 42362
 
5.6%
h 37172
 
4.9%
l 30174
 
4.0%
Other values (73) 247526
32.8%
Common
ValueCountFrequency (%)
153689
75.6%
. 26647
 
13.1%
! 5784
 
2.8%
' 5674
 
2.8%
, 4226
 
2.1%
- 1927
 
0.9%
? 1161
 
0.6%
0 802
 
0.4%
" 582
 
0.3%
1 516
 
0.3%
Other values (42) 2182
 
1.1%
Han
ValueCountFrequency (%)
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
Other values (11) 11
52.4%
Tamil
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Hiragana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 958283
> 99.9%
Punctuation 280
 
< 0.1%
None 110
 
< 0.1%
CJK 21
 
< 0.1%
Tamil 5
 
< 0.1%
Hiragana 5
 
< 0.1%
Katakana 4
 
< 0.1%
IPA Ext 2
 
< 0.1%
Modifier Letters 2
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
153689
16.0%
e 94415
 
9.9%
t 57269
 
6.0%
o 56567
 
5.9%
a 51474
 
5.4%
n 47498
 
5.0%
i 46037
 
4.8%
r 44994
 
4.7%
s 42362
 
4.4%
h 37172
 
3.9%
Other values (78) 326806
34.1%
Punctuation
ValueCountFrequency (%)
148
52.9%
82
29.3%
15
 
5.4%
14
 
5.0%
9
 
3.2%
8
 
2.9%
4
 
1.4%
None
ValueCountFrequency (%)
é 18
16.4%
ä 16
14.5%
ö 8
 
7.3%
á 6
 
5.5%
ó 6
 
5.5%
ü 5
 
4.5%
í 5
 
4.5%
ı 5
 
4.5%
· 4
 
3.6%
ć 3
 
2.7%
Other values (26) 34
30.9%
IPA Ext
ValueCountFrequency (%)
ə 2
100.0%
Tamil
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
CJK
ValueCountFrequency (%)
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
Other values (11) 11
52.4%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Modifier Letters
ValueCountFrequency (%)
ˌ 1
50.0%
ˈ 1
50.0%
Hiragana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Math Operators
ValueCountFrequency (%)
1
100.0%

title
Text

Distinct42198
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:47.840523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length105
Median length79
Mean length16.70206483
Min length1

Characters and Unicode

Total characters757923
Distinct characters287
Distinct categories17 ?
Distinct scripts7 ?
Distinct blocks12 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39870 ?
Unique (%)87.9%

Sample

1st rowToy Story
2nd rowJumanji
3rd rowGrumpier Old Men
4th rowWaiting to Exhale
5th rowFather of the Bride Part II
ValueCountFrequency (%)
the 14556
 
10.7%
of 4930
 
3.6%
a 2241
 
1.6%
in 1693
 
1.2%
and 1631
 
1.2%
to 1054
 
0.8%
757
 
0.6%
man 666
 
0.5%
love 664
 
0.5%
for 601
 
0.4%
Other values (24354) 107397
78.9%
2023-06-29T19:28:48.249525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90833
 
12.0%
e 76254
 
10.1%
a 48947
 
6.5%
o 45672
 
6.0%
n 40820
 
5.4%
r 40022
 
5.3%
i 39767
 
5.2%
t 36724
 
4.8%
s 29521
 
3.9%
h 28522
 
3.8%
Other values (277) 280841
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 534181
70.5%
Uppercase Letter 117274
 
15.5%
Space Separator 90833
 
12.0%
Other Punctuation 10490
 
1.4%
Decimal Number 3850
 
0.5%
Dash Punctuation 981
 
0.1%
Close Punctuation 87
 
< 0.1%
Open Punctuation 85
 
< 0.1%
Final Punctuation 38
 
< 0.1%
Other Letter 25
 
< 0.1%
Other values (7) 79
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 76254
14.3%
a 48947
9.2%
o 45672
 
8.5%
n 40820
 
7.6%
r 40022
 
7.5%
i 39767
 
7.4%
t 36724
 
6.9%
s 29521
 
5.5%
h 28522
 
5.3%
l 25926
 
4.9%
Other values (121) 122006
22.8%
Uppercase Letter
ValueCountFrequency (%)
T 16021
13.7%
S 10338
 
8.8%
M 8034
 
6.9%
B 7659
 
6.5%
C 7165
 
6.1%
A 6786
 
5.8%
D 6335
 
5.4%
L 5872
 
5.0%
H 5170
 
4.4%
W 5166
 
4.4%
Other values (65) 38728
33.0%
Other Letter
ValueCountFrequency (%)
چ 2
 
8.0%
ه 2
 
8.0%
ی 2
 
8.0%
ک 2
 
8.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
ª 1
 
4.0%
Other values (11) 11
44.0%
Other Punctuation
ValueCountFrequency (%)
: 3718
35.4%
' 2505
23.9%
. 1603
15.3%
, 1134
 
10.8%
! 647
 
6.2%
& 458
 
4.4%
? 269
 
2.6%
/ 79
 
0.8%
* 19
 
0.2%
# 13
 
0.1%
Other values (8) 45
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 861
22.4%
1 697
18.1%
0 616
16.0%
3 482
12.5%
9 230
 
6.0%
4 229
 
5.9%
5 225
 
5.8%
7 193
 
5.0%
8 161
 
4.2%
6 156
 
4.1%
Math Symbol
ValueCountFrequency (%)
+ 17
70.8%
× 3
 
12.5%
1
 
4.2%
= 1
 
4.2%
1
 
4.2%
1
 
4.2%
Other Number
ValueCountFrequency (%)
½ 12
63.2%
² 3
 
15.8%
³ 2
 
10.5%
1
 
5.3%
1
 
5.3%
Other Symbol
ValueCountFrequency (%)
° 3
37.5%
2
25.0%
1
 
12.5%
1
 
12.5%
1
 
12.5%
Currency Symbol
ValueCountFrequency (%)
$ 18
85.7%
¢ 2
 
9.5%
£ 1
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 966
98.5%
15
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 82
94.3%
] 5
 
5.7%
Open Punctuation
ValueCountFrequency (%)
( 80
94.1%
[ 5
 
5.9%
Final Punctuation
ValueCountFrequency (%)
37
97.4%
1
 
2.6%
Initial Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
90833
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Format
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 650940
85.9%
Common 106443
 
14.0%
Cyrillic 346
 
< 0.1%
Greek 170
 
< 0.1%
Arabic 11
 
< 0.1%
Katakana 8
 
< 0.1%
Han 5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 76254
 
11.7%
a 48947
 
7.5%
o 45672
 
7.0%
n 40820
 
6.3%
r 40022
 
6.1%
i 39767
 
6.1%
t 36724
 
5.6%
s 29521
 
4.5%
h 28522
 
4.4%
l 25926
 
4.0%
Other values (107) 238765
36.7%
Common
ValueCountFrequency (%)
90833
85.3%
: 3718
 
3.5%
' 2505
 
2.4%
. 1603
 
1.5%
, 1134
 
1.1%
- 966
 
0.9%
2 861
 
0.8%
1 697
 
0.7%
! 647
 
0.6%
0 616
 
0.6%
Other values (50) 2863
 
2.7%
Cyrillic
ValueCountFrequency (%)
е 32
 
9.2%
о 32
 
9.2%
а 29
 
8.4%
н 24
 
6.9%
и 23
 
6.6%
р 22
 
6.4%
к 17
 
4.9%
с 15
 
4.3%
л 14
 
4.0%
в 14
 
4.0%
Other values (38) 124
35.8%
Greek
ValueCountFrequency (%)
α 20
 
11.8%
ι 14
 
8.2%
ο 14
 
8.2%
τ 9
 
5.3%
ά 8
 
4.7%
λ 8
 
4.7%
ρ 8
 
4.7%
ν 7
 
4.1%
ε 6
 
3.5%
ς 6
 
3.5%
Other values (32) 70
41.2%
Katakana
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Arabic
ValueCountFrequency (%)
چ 2
18.2%
ه 2
18.2%
ی 2
18.2%
ک 2
18.2%
س 1
9.1%
ا 1
9.1%
ج 1
9.1%
Han
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 756358
99.8%
None 1124
 
0.1%
Cyrillic 346
 
< 0.1%
Punctuation 62
 
< 0.1%
Arabic 11
 
< 0.1%
Katakana 8
 
< 0.1%
CJK 5
 
< 0.1%
Misc Symbols 3
 
< 0.1%
Letterlike Symbols 2
 
< 0.1%
Math Operators 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90833
 
12.0%
e 76254
 
10.1%
a 48947
 
6.5%
o 45672
 
6.0%
n 40820
 
5.4%
r 40022
 
5.3%
i 39767
 
5.3%
t 36724
 
4.9%
s 29521
 
3.9%
h 28522
 
3.8%
Other values (76) 279276
36.9%
None
ValueCountFrequency (%)
é 218
19.4%
ä 127
 
11.3%
ö 55
 
4.9%
è 53
 
4.7%
ô 44
 
3.9%
ü 39
 
3.5%
ó 37
 
3.3%
á 35
 
3.1%
ı 35
 
3.1%
í 33
 
2.9%
Other values (108) 448
39.9%
Punctuation
ValueCountFrequency (%)
37
59.7%
15
24.2%
5
 
8.1%
2
 
3.2%
1
 
1.6%
1
 
1.6%
1
 
1.6%
Cyrillic
ValueCountFrequency (%)
е 32
 
9.2%
о 32
 
9.2%
а 29
 
8.4%
н 24
 
6.9%
и 23
 
6.6%
р 22
 
6.4%
к 17
 
4.9%
с 15
 
4.3%
л 14
 
4.0%
в 14
 
4.0%
Other values (38) 124
35.8%
Arabic
ValueCountFrequency (%)
چ 2
18.2%
ه 2
18.2%
ی 2
18.2%
ک 2
18.2%
س 1
9.1%
ا 1
9.1%
ج 1
9.1%
Misc Symbols
ValueCountFrequency (%)
2
66.7%
1
33.3%
CJK
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Letterlike Symbols
ValueCountFrequency (%)
1
50.0%
1
50.0%
Math Operators
ValueCountFrequency (%)
1
50.0%
1
50.0%
Katakana
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Arrows
ValueCountFrequency (%)
1
100.0%

vote_average
Real number (ℝ)

ZEROS 

Distinct92
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.62407942
Minimum0
Maximum10
Zeros2947
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:48.395493image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median6
Q36.8
95-th percentile7.8
Maximum10
Range10
Interquartile range (IQR)1.8

Descriptive statistics

Standard deviation1.915380993
Coefficient of variation (CV)0.3405679135
Kurtosis2.542209793
Mean5.62407942
Median Absolute Deviation (MAD)0.9
Skewness-1.524484076
Sum255215.1
Variance3.66868435
MonotonicityNot monotonic
2023-06-29T19:28:48.528525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2947
 
6.5%
6 2463
 
5.4%
5 1998
 
4.4%
7 1884
 
4.2%
6.5 1722
 
3.8%
6.3 1603
 
3.5%
5.5 1381
 
3.0%
5.8 1369
 
3.0%
6.4 1350
 
3.0%
6.7 1342
 
3.0%
Other values (82) 27320
60.2%
ValueCountFrequency (%)
0 2947
6.5%
0.5 13
 
< 0.1%
0.7 1
 
< 0.1%
1 103
 
0.2%
1.1 1
 
< 0.1%
ValueCountFrequency (%)
10 185
0.4%
9.8 1
 
< 0.1%
9.6 1
 
< 0.1%
9.5 18
 
< 0.1%
9.4 3
 
< 0.1%

vote_count
Real number (ℝ)

ZEROS 

Distinct1820
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110.0899315
Minimum0
Maximum14075
Zeros2849
Zeros (%)6.3%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:48.658523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median10
Q334
95-th percentile434
Maximum14075
Range14075
Interquartile range (IQR)31

Descriptive statistics

Standard deviation491.7272948
Coefficient of variation (CV)4.466596429
Kurtosis150.9384834
Mean110.0899315
Median Absolute Deviation (MAD)8
Skewness10.44112465
Sum4995771
Variance241795.7324
MonotonicityNot monotonic
2023-06-29T19:28:48.784526image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3243
 
7.1%
2 3127
 
6.9%
0 2849
 
6.3%
3 2785
 
6.1%
4 2478
 
5.5%
5 2097
 
4.6%
6 1747
 
3.8%
7 1570
 
3.5%
8 1359
 
3.0%
9 1194
 
2.6%
Other values (1810) 22930
50.5%
ValueCountFrequency (%)
0 2849
6.3%
1 3243
7.1%
2 3127
6.9%
3 2785
6.1%
4 2478
5.5%
ValueCountFrequency (%)
14075 1
< 0.1%
12269 1
< 0.1%
12114 1
< 0.1%
12000 1
< 0.1%
11444 1
< 0.1%

release_year
Real number (ℝ)

Distinct135
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1991.882236
Minimum1874
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:48.919525image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1874
5-th percentile1941
Q11978
median2001
Q32010
95-th percentile2015
Maximum2020
Range146
Interquartile range (IQR)32

Descriptive statistics

Standard deviation24.05498602
Coefficient of variation (CV)0.01207651014
Kurtosis0.8403296365
Mean1991.882236
Median Absolute Deviation (MAD)12
Skewness-1.224939659
Sum90389624
Variance578.6423525
MonotonicityNot monotonic
2023-06-29T19:28:49.048526image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2014 1975
 
4.4%
2015 1905
 
4.2%
2013 1889
 
4.2%
2012 1723
 
3.8%
2011 1667
 
3.7%
2016 1604
 
3.5%
2009 1586
 
3.5%
2010 1501
 
3.3%
2008 1473
 
3.2%
2007 1320
 
2.9%
Other values (125) 28736
63.3%
ValueCountFrequency (%)
1874 1
< 0.1%
1878 1
< 0.1%
1883 1
< 0.1%
1887 1
< 0.1%
1888 2
< 0.1%
ValueCountFrequency (%)
2020 1
 
< 0.1%
2018 5
 
< 0.1%
2017 532
 
1.2%
2016 1604
3.5%
2015 1905
4.2%

return
Real number (ℝ)

SKEWED  ZEROS 

Distinct5232
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean659.9991483
Minimum0
Maximum12396383
Zeros39998
Zeros (%)88.1%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2023-06-29T19:28:49.189494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.53534128
Maximum12396383
Range12396383
Interquartile range (IQR)0

Descriptive statistics

Standard deviation74690.82512
Coefficient of variation (CV)113.1680629
Kurtosis20674.32378
Mean659.9991483
Median Absolute Deviation (MAD)0
Skewness138.3340992
Sum29950101.35
Variance5578719356
MonotonicityNot monotonic
2023-06-29T19:28:49.329493image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39998
88.1%
1 20
 
< 0.1%
2 12
 
< 0.1%
4 11
 
< 0.1%
5 8
 
< 0.1%
3 7
 
< 0.1%
2.5 7
 
< 0.1%
1.333333333 7
 
< 0.1%
1.5 6
 
< 0.1%
7 4
 
< 0.1%
Other values (5222) 5299
 
11.7%
ValueCountFrequency (%)
0 39998
88.1%
5.217391304 × 10-71
 
< 0.1%
7.5 × 10-71
 
< 0.1%
9.375 × 10-71
 
< 0.1%
1.499133126 × 10-61
 
< 0.1%
ValueCountFrequency (%)
12396383 1
< 0.1%
8500000 1
< 0.1%
4197476.625 1
< 0.1%
2755584 1
< 0.1%
1018619.283 1
< 0.1%